During the manufacture of different kinds of articles, one or more visual inspections are often performed, so that defects, such as scratches and stains which only manifest themselves visually, can be detected. In many instances, visual inspection of articles during their manufacture is performed by one or more commercially available machine vision systems. Typical machine vision systems are highly accurate, usually much more so than a human inspector whose accuracy will be influenced by factors such as eye strain, fatigue and boredom, which are thus avoided by the use of a machine vision system.
While present day machine vision systems are useful for detecting defects on a wide variety of articles, such systems sometimes incur difficulties in detecting specific defects on certain types of articles. For example, it has not been feasible to use present day automated machine vision systems to detect defects such as edge cracks on an exposed surface of a semiconductor chip surrounded by a volume of bonding material. This is because many present day systems cannot always accurately differentiate between the edge of the chip and the bonding material. Typically, the chip has a textured surface (i.e., the surface contains a large number of features), as does the bonding material, which is typically a eutectic, like solder. Thus, to the machine vision system, the chip and the surrounding bonding material may appear very similar.
Thus, there is a need for a technique for differentiating between a planar textured surface on an article, such as the exposed surface on a semiconductor chip, from a background region, such as a volume of bonding material surrounding the chip.